Recent efforts to produce tools to effectively control the dynamics of complex networked systems draw from control theory, numerical methods and, more recently, network science and machine learning. A dynamical system is controllable if by intervening on the state of individual nodes the system as a whole can be driven from any initial state to a desirable state, within finite time [1]}.
This notion of control finds application in blueengineered systems but also biological networks, blueand is often referred to as stabilization.
